Non-Orthogonal Multiple Access (NOMA) is able, in principle, to achieve a higher throughput than orthogonal multiple access (OMA), which includes conventional multiple access schemes like time division multiple access (TDMA), Orthogonal code division multiple access (OCDMA), and Orthogonal frequency division multiple access (OFDMA). Recently, NOMA gained a significant interest in the technical community and in standardization for 5G cellular networks and beyond. Following the trend of 4G, the 3GPP has decided that multiple access for Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communications (URLLC) traffic in 5G will be based on OFDMA, but NOMA still stands as a strong candidate for Massive Machine-Type Communications (mMTC).
A common feature of NOMA schemes is to multiplex user signals in the power domain, i.e., to superpose two or more user signals and transmit them during the same time slot and the same frequency band. Another common feature is the use of successive interference cancellation (SIC) to handle the resulting interference. FIG. 1 illustrates an example of a downlink with NOMA.
In this example, User 2 signal (11) has a higher power than User 1 signal (10), and therefore User 2 (12) can detect its signal in the presence of interference from User 1 (13). But User 1 cannot detect its signal directly. User 1 must first detect the strong signal of User 2, subtract this from the received signal, and then detect its signal in the presence of residual interference (using SIC 14) from User 2. This scheme imposes a strong power imbalance between user signals so that the SIC receiver (14) can work properly. The bit error rate (BER) performance will be far from that achievable in the absence of interference.
Another NOMA technique uses two sets of orthogonal signal waveforms that are stacked (added) together to accommodate two groups of users. The stacking is such that no interference arises between users of the same group, but each user is subject to interference from all users of the other group. Two-stage iterative interference cancellation is used to handle the noise between the two groups as would be understood. For example, the first signal set (the primary signal set) is used in full, and the second signal set is used only partially. In a first stage, preliminary decisions are made on the symbols transmitted by primary set users in the presence of interference from secondary set users. In a second stage, the interference of primary set users is synthesized based on these decisions and is subtracted from the received signal. After this interference cancellation step, first-iteration decisions are made on the symbols transmitted by secondary set users. Then, the interference of secondary set users is synthesized based on these decisions, it is subtracted from the received signal, and second-iteration decisions are made on the symbols transmitted by first set users, and the process continues in this way. As would be understood, depending on the number of users in the secondary set, two iterations may be sufficient, or 4 to 5 iterations may be required. ‘Sufficient’ is measured based on how many users we have in the secondary set. For example, if the Primary set is used in full and only a small subset of the secondary set is used, a relatively small number of iterations, for example two may be sufficient to detect all signals. If there are more users with resources from the secondary set, then more iterations might be needed to detect all signals. In the end, a ‘sufficient’ number of iterations is judged on performance of the interference cancellation.
No power or energy imbalance is required between different user signals with this technique.
A development of this technique is to superpose a plurality of MC-CDMA signals that are spread over the entire band onto OFDMA signals such that each MC-CDMA signal interferes with all OFDMA signals. Iterative interference cancellation is used to deal with that interference as explained above. Mathematical analysis of this technique shows that the number of MC-CDMA symbols spread over N subcarriers should be limited to IN in order to achieve bit error rate (BER) performance close to the BER of the original OFDMA signal. However, even when the number of MC-CDMA symbols complies with this bound, the performance gap from the original OFDMA BER is a function of the number of MC-CDMA symbols superposed to the OFDMA symbols, and this performance degradation is generally not negligible. Another disadvantage is that the two-stage iterative interference cancellation receiver used provides different BER performance results for the original OFDMA symbols and for the MC-CDMA symbols superposed to them. This is because the decisions on the OFDMA symbols (stage 1) are made in the first stage of the receiver, and those on the MC-CDMA (stage 2) symbols are made in the second stage. The interference values affecting these decisions are different, and therefore the performance degradations from the ideal BER curves are also different.
Accordingly, there is a need to provide an improved NOMA scheme whereby communication channel capacity is increased while maintaining signal to noise, and energy performance.